(window.webpackJsonp=window.webpackJsonp||[]).push([[35],{102:function(e,n,t){"use strict";t.r(n),t.d(n,"frontMatter",(function(){return i})),t.d(n,"metadata",(function(){return p})),t.d(n,"toc",(function(){return o})),t.d(n,"default",(function(){return m}));var r=t(3),a=t(7),s=(t(0),t(144)),i={title:"Experiment REST API"},p={unversionedId:"api/experiment",id:"api/experiment",isDocsHomePage:!1,title:"Experiment REST API",description:"\x3c!--",source:"@site/docs/api/experiment.md",slug:"/api/experiment",permalink:"/docs/api/experiment",editUrl:"https://github.com/apache/submarine/edit/master/website/docs/api/experiment.md",version:"current",sidebar:"api",previous:{title:"Environment REST API",permalink:"/docs/api/environment"},next:{title:"Experiment Template REST API",permalink:"/docs/api/experiment-template"}},o=[{value:"Create Experiment (Using Anonymous/Embedded Environment)",id:"create-experiment-using-anonymousembedded-environment",children:[]},{value:"Create Experiment (Using 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experiment"),Object(s.b)("p",null,Object(s.b)("inlineCode",{parentName:"p"},"PATCH /api/v1/experiment/{id}")),Object(s.b)("p",null,Object(s.b)("strong",{parentName:"p"},"Example Request:")),Object(s.b)("pre",null,Object(s.b)("code",{parentName:"pre",className:"language-sh"},'curl -X PATCH -H "Content-Type: application/json" -d \'\n{\n  "meta": {\n    "name": "tf-mnist-json",\n    "namespace": "default",\n    "framework": "TensorFlow",\n    "cmd": "python /var/tf_mnist/mnist_with_summaries.py --log_dir=/train/log --learning_rate=0.01 --batch_size=150",\n      "envVars": {\n      "ENV_1": "ENV1"\n    }\n  },\n  "environment": {\n    "image": "apache/submarine:tf-mnist-with-summaries-1.0"\n  },\n  "spec": {\n    "Ps": {\n      "replicas": 1,\n      "resources": "cpu=1,memory=1024M"\n    },\n    "Worker": {\n      "replicas": 2,\n      "resources": "cpu=1,memory=2048M"\n    }\n  }\n}\n\' 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"logContent": [\n            {\n                "podName": "pytorch-dist-mnist-gloo-master-0",\n                "podLog": "Using distributed PyTorch with gloo backend\\nDownloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz\\nDownloading http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz\\nDownloading http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz\\nDownloading http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz\\nProcessing...\\nDone!\\nTrain Epoch: 1 [0/60000 (0%)]\\tloss=2.3000\\nTrain Epoch: 1 [640/60000 (1%)]\\tloss=2.2135\\nTrain Epoch: 1 [1280/60000 (2%)]\\tloss=2.1704\\nTrain Epoch: 1 [1920/60000 (3%)]\\tloss=2.0766\\nTrain Epoch: 1 [2560/60000 (4%)]\\tloss=1.8679\\nTrain Epoch: 1 [3200/60000 (5%)]\\tloss=1.4135\\nTrain Epoch: 1 [3840/60000 (6%)]\\tloss=1.0003\\nTrain Epoch: 1 [4480/60000 (7%)]\\tloss=0.7762\\nTrain Epoch: 1 [5120/60000 (9%)]\\tloss=0.4598\\nTrain Epoch: 1 [5760/60000 (10%)]\\tloss=0.4860\\nTrain Epoch: 1 [6400/60000 (11%)]\\tloss=0.4389\\nTrain Epoch: 1 [7040/60000 (12%)]\\tloss=0.4084\\nTrain Epoch: 1 [7680/60000 (13%)]\\tloss=0.4602\\nTrain Epoch: 1 [8320/60000 (14%)]\\tloss=0.4289\\nTrain Epoch: 1 [8960/60000 (15%)]\\tloss=0.3990\\nTrain Epoch: 1 [9600/60000 (16%)]\\tloss=0.3852\\n"\n            },\n            {\n                "podName": "pytorch-dist-mnist-gloo-worker-0",\n                "podLog": "Using distributed PyTorch with gloo backend\\nDownloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz\\nDownloading http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz\\nDownloading http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz\\nDownloading http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz\\nProcessing...\\nDone!\\nTrain Epoch: 1 [0/60000 (0%)]\\tloss=2.3000\\nTrain Epoch: 1 [640/60000 (1%)]\\tloss=2.2135\\nTrain Epoch: 1 [1280/60000 (2%)]\\tloss=2.1704\\nTrain Epoch: 1 [1920/60000 (3%)]\\tloss=2.0766\\nTrain Epoch: 1 [2560/60000 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